The present invention relates to signal signature analysis for rotating machinery.
The continuous (or at least frequent) monitoring, detection and analysis of machine vibration can be helpful in maintaining rotating machinery, such as production-line critical devices. Certain vibrations in machinery are indicative of the operating condition of the machine and may be used to monitor the machine, such as to determine when maintenance is needed. Vibration signal processing techniques have been implemented that identify certain vibration events and distinguish other machinery vibrations in the harsh signal environment common to rotating machines.
A conventional approach to identifying vibration signal events are noise-cleaning techniques. These techniques filter out spectral vibrational regimes that carry nominal or no information regarding the vibration data of interest e.g., vibration data of abnormal machine operation. Noise-cleaning techniques typically identify vibration signal signatures that are of interest and/or that indicate a potential machine problem or operating condition. The vibration signal signatures are identified using signal templates that are specific to a particular vibration signal signature and filter out other vibrations. The signal templates are typically exemplary excerpts of vibration signals of interest. Signal templates are used to identify vibration signal events that are similar to the vibration signal defined by the template.
A difficulty with signal templates is that they are specific to a single machine or machine model. The signal signature(s) for each rotating machine tends to exhibit some difference(s) with respect to the signal signatures of other rotating machines. To create the filtering templates for noise-cleaning, the templates are typically uniquely designed for each machine. The development of templates may involve extensive vibration analysis to properly dichotomize the vibration data into an information-bearing regime and a noise regime. There is therefore a long-felt need for improved techniques for vibration signal analysis that overcome the significant problems in existing noise-filtering techniques.